Replicated Sampling
Replicated sampling implies a sample design in which “two or more sub-samples are drawn and processed completely independent of each other” It was first introduced by “Mahalnobis” in 1936, who used the term inter-penetrating sub-samples.
In replicated sampling, several random sub-samples are selected from the population instead of one full sample. All the sub-samples have the same design and each one of them is a self-contained sample of the population. For example, take the case of a random sample of 10 households. This sample may be divided into, say, 10 equal sub-samples to be assigned to 10 interviewers. Thus, each interviewer may be required to collect information from 10 households.
A replicated sample is particularly chosen on account of the convenience it affords in the calculation of standard error. In many complex sample designs, the calculation of standard error becomes too laborious. Selecting a replicated sample design can considerably reduce this difficulty. However, in modem times when computers are being increasingly used, the ease in calculating standard error has made it somewhat less important. Apart from this advantage, there are certain other advantages of replicated sampling. First, if the size of a sample is too large, it may be advisable to split it up into two or more sub-samples. One sub-sample may be used to get the advanced results of the survey. Second, replicated sampling can indicate the non-sampling errors.
However, replicated sampling would not be helpful in undertaking a detailed investigation of bias as the numbers in the separate sub-samples tend to be small Further, such samples do not reveal any systematic errors that may be more or less common to all interviewers and the compensating errors which cancel each other out over an interviewer’s assignment.
Apart from the above limitations, replicated samples have other disadvantages If personal interviews are to be conducted, replicated samples turn out to be costlier Likewise, tabulation costs would be higher than in the case of a single large sample Finally, replicated samples are more complex to administer.
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